Stratigraphic Trap Recognition via Orbital Cyclicity Analysis
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Solution Overview
Problem
Current gamma ray logging methods lack an effective way to determine the presence of stratigraphic traps, which are crucial for identifying hydrocarbon reservoirs, as they rely solely on geological data without considering the impact of Earth's orbital parameters on sedimentary patterns.
Innovation Solution
A method that involves obtaining gamma ray log datasets, determining the geological time period, calculating the spectrum of Earth's orbital parameters (eccentricity, obliquity, and precession), and identifying peak frequencies to quantify orbital cycles, which are then used to determine the presence of stratigraphic traps by analyzing differences in orbital cycles between wells.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If gamma ray logging methods rely solely on geological data without orbital parameters, then the method is simple and easy to operate, but the accuracy of stratigraphic trap identification is insufficient
Solution Approach 1:
The patent combines gamma ray logging data with Earth's orbital parameter data (eccentricity, obliquity, precession) to create a hybrid analysis method. This merging of geological data with astronomical data enables more accurate stratigraphic trap identification by capturing both sedimentary characteristics and orbital cycle influences on sedimentation patterns.
Solution Approach 2:
The patent introduces spectral analysis as an intermediary method to bridge gamma ray logging data and orbital parameter data. By transforming both datasets into spectral domains and comparing their frequency characteristics, the method identifies correlations between orbital cycles and sedimentary patterns without requiring direct physical measurement of orbital effects.
2Measurement precision
If gamma ray logging methods use only geological data, then the data processing is quick and efficient, but the determination of hydrocarbon potential is less accurate
Solution Approach 1:
The patent performs preliminary spectral analysis on orbital parameter data to pre-calculate expected frequency signatures for different geological time periods. This allows the method to quickly compare processed gamma ray logs against pre-computed orbital spectra, reducing real-time processing requirements while maintaining high accuracy in hydrocarbon potential determination.
3Measurement precision
If orbital parameters are integrated with gamma ray logging, then the accuracy of sedimentary pattern analysis is improved, but the device complexity and computational requirements increase
Solution Approach 1:
The patent replaces complex physical measurement systems with computational spectral analysis. Instead of requiring sophisticated instruments to directly measure orbital influences on sedimentation, the method uses mathematical transformations (Fast Fourier Transform) to extract cyclical patterns from existing gamma ray logging data and compares them with calculated orbital parameter spectra.
Data Source
AI summary
A method of determining a presence of stratigraphic traps includes obtaining a Gamma ray (GR) log dataset. The GR log dataset includes values for a plurality of wells in an area of interest. The method includes determining a geological time period corresponding to a depth in the GR log dataset; determining a spectrum of Earth's orbital parameters corresponding to the geological time period; determining peak frequencies of the spectrum of Earth's orbital parameters; and determining a quantity of orbital cycles per well in the area of interest. The spectrum of Earth's orbital parameters includes parameters for eccentricity, obliquity, and precession. The orbital cycles may be reflected as sedimentary patterns in a geologic record. The method includes determining a presence of stratigraphic traps, based, at least in part, on differences in quantities of orbital cycles between one or more wells in the area of interest.